Synthetic or Organic Data?

CB Insights Report on AI Trends Report 2022 (https://bit.ly/3XSpPDU) opens its Introduction with “The era of machine learning has arrived”. Should it not be the Era of Human Learning has arrived?

Because we have so much to unlearn from the conditionality of that we have imposed on the collective thinking of our societies and the life needs to be very different than what we have seen so far.

Machines can only learn what we let them learn. Are we continuing to repeat what we have done with human beings over centuries now? It would be such a tremendous waste of an estimated $66.8 Billion that reportedly AI companies have raised in 2021 and the trend continues unabated despite the “Investment Winter”.

It is quite troubling to learn that AI companies are using Synthetic Data to generate AI Models based on Pattern Recognition from the Historically Empirical (Transactional) Datasets. For one, these cannot be indicative of the Future Requirements nor can they be accurate because of a lack of exhaustiveness of data. Apparently, this is a workaround to meet the requirements of?data anonymity. Until this point in time, in any sphere of life, humans have not been afforded Data Autonomy. So this whole dance around data is more about the legality and control of the data. But it cannot be at the cost of Human Progress, can it?

Synthetic data is perhaps okay to train data sets to model Learning and Prove the Concept. But certainly not for Prototyping to Prove the Success or for Real Life Transactions to Prove the Realization of the Goals & Objectives.

We have the opportunity to employ Organic Data by using Alpha and Beta Customers in the journey of creating Intellectual Property (IP) through Modeling and Engineering. Where Data Autonomy solves the problem of Data Anonymity and Direct Consent. This is a far more straightforward and economical approach than using Synthetic Datasets that are neither directly approved nor appropriate for modeling the future.?

Using Organic Data demands the discipline and transparency of modeling new processes and generating data through engagement and experience of users, continuously optimizing the process in the pathways between Potential and Performance that rides on Value. What is being orchestrated with Synthetic Data is only the pathways between Stated Needs that turn into more urgent Wants over a period of time, riding the Wave of Trends.?

Driving the development of Generative AI with Synthetic is an absolute waste of time, money and resources. Just as much as focusing on the hype of Meta Verse. Both these areas of Technology have a significant contribution to make to the Quality of Life we lead on our Planet. Unlike the past leading up to the present, enterprise data has been two dimensional:

1. The first dimension is how a Product / Service that is created can be marketed and sold.
2. The second dimension being how the Personal Data can be manipulated to achieve the objectives of the first dimension.?

This is where the Digital Transformation sets in.

1. The first dimension has to be Modeling generative Intelligence focusing on Life Cycle of People in real life in the specific context of the renewed processes in each sphere of life and the roles the Customer Universe of Clients, Team Members (Creators), Stakeholders, Shareholders, Business Partners, Vendors, Society (Compliance & Regulators) and Technology (IOT, Sensors, Scanners, Wearables and Devices) play a role in that renewed process.?
2. The second dimension is how Products and Services can be Configured, Personalized / Industrialized and Commercialized to the first dimension.
3. The Conceptualization and Engineering of New Intellectual Property (IP) that can be Plugged and Played into the second dimension.

Privacy & Security, Distorted and Divisive Content, Chips that enable Realtime Computing through the closed loop of Creation to Consumption, Augmented Coding that extends Logic and Rules from a given context to a new generative context and Multimodal AI that recognizes Data inclusively as Text, Voice, Video and Graphics are not disparate and disjointed subjects. They are part of the Generative or Cognitive AI that need a Holistic attention. As long as this subject is approached from the unidimensional of a Business Enterprise, it is a recipe for failure.?

The process of innovation is itself faulty. Systemic Innovation is the process of establishing the new where a precedent does not exist, What we are attempting with Generative Intelligence falls in this category.?This may also be termed as the Mind 2 Market. Systems’ Innovation on the other hand is the “Out of the Box” approach where a Precedent is accelerated to deeper and wider access and affordability. Systematic Improvisation is not Innovation but just a function of Competition.

The promise of Intelligent Technology is Recursive Learning in Action. Where a Process which is the highest form of Abstraction for Data and Content transforms differentiated to a Role. The role therefore is the Identity that needs to be guarded with Authentication, Authorization, Access, Permissions and Privileges. The course of action of the role would be the source of generative AI and is organic. Scaling therefore needs to be understood differently advancing from Alpha to Beta to Theta Customers. Where Customers are People / Roles in the Alpha and Beta Stage helping Co-Create Products, Processes and Projects (Services). And a Platform carries all the three from Conceptualization to Engineering to Personalization / Industrialization and Commercialization in a Continuum.?